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Numerical weather prediction and climate models encounter challenges in accurately representing flow regimes in the stably stratified atmospheric boundary layer and the transitions between them, leading to an inadequate depiction of regime occupation statistics. As a consequence, existing models exhibit significant biases in near-surface temperatures at high latitudes. To explore inherent uncertainties in modeling regime transitions, the response of the near-surface temperature inversion to transient small-scale phenomena is analyzed based on a stochastic modeling approach. A sensitivity analysis is conducted by augmenting a conceptual model for near-surface temperature inversions with randomizations that account for different types of model uncertainty. The stochastic conceptual model serves as a tool to systematically investigate what types of unsteady flow features, and in what contexts, may trigger abrupt transitions in the mean boundary layer state. The findings show that the incorporation of enhanced mixing, a common practice in numerical weather prediction models, blurs the two regime characteristic of the stably stratified atmospheric boundary layer. Simulating intermittent turbulence is shown to provide a potential workaround for this issue. Including key uncertainty in models could lead to a better statistical representation of the regimes in long-term climate simulation. This would help to improve our understanding and the forecasting of climate change especially in high-latitude regions.

The number of published data from the Earth System Sciences is steadily rising. Even though many of the datasets are published with a DOI, only a part of them complies with the FAIR Data Principles [1]. As in many scientific disciplines, there are a variety of activities in Earth System Sciences that address the FAIRness of the data. What has not been sufficiently investigated and dealt with so far is the easy discoverability and re-use of quality-checked data. This aspect is taken up by the EASYDAB service [2]. The Earth System Data Branding (EASYDAB) was developed within the BMBF [3] funded project AtMoDat [4]. The branding can be adopted by institutions running a data repository. Chosen Earth system research datasets published with a DataCite [5] DOI can be highlighted with a logo on the landing page [6]. The EASYDAB logo indicates that the datasets have an open [7] license, comply with the FAIR Data Principles to the best knowledge possible, and were reviewed by the responsible repository for compliance with a quality guideline. The first quality guideline made for EASYDAB is the ATMODAT standard [8]. The standard incorporates concrete recommendations and requirements related to the maturity, publication and enhanced FAIRness of atmospheric model data. The requirements are for rich metadata with controlled vocabularies, structured landing pages, file formats (netCDF) and the structure within files. Human- and machine-readable landing pages are a core element of the ATMODAT standard and should hold and present discipline-specific metadata on simulation and variable levels. The integration of standards from other disciplines in the Earth System Sciences into EASYDAB is desirable if they achieve a comparably high quality of the published data as defined in the ATMODAT standard. EASYDAB highlights the efforts of repositories to publish data with high maturity. It enables users to easily find reviewed, high-quality data. 1: Wilkinson et al., 2016: https://doi.org/10.1038/sdata.2016.18 2: https://www.easydab.de 3: Federal Ministry of Education and Research https://www.bmbf.de/en/index.html 4: https://www.atmodat.de 5: https://DataCite.org 6: https://support.datacite.org/docs/landing-pages 7: https://opendefinition.org/licenses/ 8: https://cera-www.dkrz.de/WDCC/ui/cerasearch/entry?acronym=atmodat_standard_en_v3_0, {"references":["Wilkinson et al. (2016) https://doi.org/10.1038/sdata.2016.18","Ganske et al. (2021) https://doi.org/10.35095/WDCC/atmodat_standard_en_v3_0","Ganske et al. (2021) https://doi.org/10.35095/WDCC/EASYDAB_Guideline_v1.0"]}

The Earth System Data Branding (EASYDAB) was developed within the BMBF funded project AtMoDat. EASYDAB requires that the datasets have an open license,comply with the FAIR Data Principles, and were reviewed by the responsible repository for compliance with a quality guideline. Earth system research datasets published with a DataCite DOI that fulfil the EASYDAB quality requirements can be highlighted with an EASYDAB logo on the landing page. Using the EASYDAB label, repositories can indicate that they carefully curated datasets with FAIR principles in mind. Researchers can more easily find and evaluate well-described datasets.

The Earth System Data Branding (EASYDAB) was developed within the BMBF funded project AtMoDat. EASYDAB requires that the datasets have an open license, comply with the FAIR Data Principles, and were reviewed by the responsible repository for compliance with a quality guideline. Earth system research datasets published with a DataCite DOI that fulfil the EASYDAB quality requirements can be highlighted with an EASYDAB logo on the landing page. Using the EASYDAB label, repositories can indicate that they carefully curate datasets with FAIR principles in mind. Researchers can more easily find and evaluate well-described datasets.

Project: Literature - Literature e.g. grey literature Summary: Within the AtMoDat project (Atmospheric Model Data), a standard has been developed which is meant for improving the FAIRness of atmospheric model data published in repositories. The ATMODAT standard includes concrete recommendations related to the maturity, publication and enhanced FAIRness of atmospheric model data. The suggestions include requirements for rich metadata with controlled vocabularies, structured landing pages, file formats (netCDF) and the structure within files. Human- and machine readable landing pages are a core element of this standard, and should hold and present discipline-specific metadata on simulation and variable level. This standard is an updated and translated version of "Bericht über initialen Kernstandard und Kurationskriterien des AtMoDat Projektes (v2.4)

Bei Klimasimulationen werden große Mengen an Daten erzeugt. Aus diesem Grund können in der Regel nicht alle Ergebnisse einer Simulation eines Klimamodells von einer Forschungsgruppe alleine ausgewertet werden. Beim Coupled Model Intercomparison Projekt (CMIP) wird daher ein Fokus darauf gelegt, dass auch andere Forschungsgruppen die Daten auswerten können. Deshalb gibt es genaue Vorgaben, wie diese Daten zu beschreiben und zu formatieren sind. Zudem werden viele dieser Datensätze mit einem DOI (Digital Object Identifier) versehen. Dies alles erleichtert die Suche und Weiterverarbeitung der Daten. Allerdings gibt es weitaus mehr als CMIP Daten, die für die Klimaforschung wichtig sind. Viele Ergebnisse von z.B. regionalen Klimamodellen oder Stadtklimamodellen werden nicht veröffentlicht, obwohl von den Datenerzeugern nur ein Bruchteil der Ergebnisse ausgewertet werden kann. Deshalb drängen viele Förderer auf eine Veröffentlichung der Daten in einem Repositorium. Aber auch in diesem Fall können sie oft nicht weiterverwendet werden. Die Gründe sind vielfältig: Unzureichende Metadaten Mangelnde Auffindbarkeit, z.B. durch Suchmaschinen Fehlende Rechte zur Weiterverarbeitung Fehlende Qualitätskontrolle Das BMBF geförderte Projekt AtMoDat (https://www.ATMODAT.de) wurde 2019 gestartet, um die Veröffentlichung von Atmosphärischen Modelldaten zu stärken und zu verbessern. Eine Methode ist dabei die Einhaltung der FAIR-Prinzipien - Findable, Accessible, Interoperable, Reusable (siehe Wilkinson et al., 2016). Zudem sollten alle Daten mit einem DataCite DOI veröffentlicht werden, um die Auffindbarkeit und Zitierbarkeit zu verbessern. Eine Anleitung, wie man dabei vorgehen sollte, findet sich in dem Standard, der im AtMoDat-Projekt entwickelt wurde. Der ATMODAT-Standard ist leicht umzusetzen und beinhaltet genaue Vorgaben für die Metadaten des DOI, die Landing Page und die Header der netCDF-Dateien. Daten, die diesem Standard genügen und dessen Einhaltung vom jeweiligen Repositorium geprüft wurde, können mit dem Earth System Data Branding (EASYDAB) versehen werden. Durch dieses Branding kann eine angemessene Qualitätssicherung der Daten durch die Nutzer sehr leicht nachvollzogen werden. Im Vortrag werden der Standard und EASYDAB vorgestellt.

Project: Presentation - Contains presentations of different types published at the WDCC. Summary: Data maturity is an important topic in data management, which is reflected by a growing number of tools and theories trying to measure it. Data maturity describes the degree of the formalization/standardization of a data object with respect to FAIRness and quality of the (meta-)data. Currently, the DataCite Metadata Schema does not provide an explicit property to link/store information on data maturity (e.g. FAIRness or quality of data/metadata). The AtMoDat project team drafted an extension to the DataCite Metadata Schema to host such information. This extension is denoted as "Data Maturity Indicator".